Disability-First Design and Creation of A Dataset Showing Private Visual Information Collected With People Who Are Blind

Tanusree Sharma, Abigale Stangl, Lotus Zhang, Yu Yun Tseng, Inan Xu, Leah Findlater, Danna Gurari, Yang Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present the design and creation of a disability-first dataset, "BIV-Priv,"which contains 728 images and 728 videos of 14 private categories captured by 26 blind participants to support downstream development of artificial intelligence (AI) models. While best practices in dataset creation typically attempt to eliminate private content, some applications require such content for model development. We describe our approach in creating this dataset with private content in an ethical way, including using props rather than participants' own private objects and balancing multi-disciplinary perspectives (e.g., accessibility, privacy, computer vision) to meet the tangible metrics (e.g., diversity, category, amount of content) to support AI innovations. We observed challenges that our participants encountered during the data collection, including accessibility issues (e.g., understanding foreground vs. background object placement) and issues due to the sensitive nature of the content (e.g., discomfort in capturing some props such as condoms around family members).

Original languageEnglish (US)
Title of host publicationCHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450394215
DOIs
StatePublished - Apr 19 2023
Event2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 - Hamburg, Germany
Duration: Apr 23 2023Apr 28 2023

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2023 CHI Conference on Human Factors in Computing Systems, CHI 2023
Country/TerritoryGermany
CityHamburg
Period4/23/234/28/23

Keywords

  • accessibility
  • blind
  • computer vision
  • dataset
  • image description
  • personal visual data
  • privacy
  • private visual content
  • visual assistance
  • visual impairments
  • visual interpretation

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

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